Results 211 to 220 of about 127,617 (265)

Unveiling the factors of aesthetic preferences with explainable AI

British Journal of Psychology, EarlyView.
Abstract The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences.
Derya Soydaner, Johan Wagemans
wiley   +1 more source

A Study on the Grip Force of Ski Gloves with Feature Data Fusion Based on GWO-BPNN Deep Learning. [PDF]

Sensors (Basel)
Ma X, Gao X, Zhang Y, Gao Y.
europepmc   +1 more source

Explanation strategies in humans versus current explainable artificial intelligence: Insights from image classification

British Journal of Psychology, EarlyView.
Abstract Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. Here, we examined human participants' attention strategies when classifying images and when explaining how they classified the images through eye‐tracking and compared their attention strategies ...
Ruoxi Qi, Yueyuan Zheng, Yi Yang, Caleb Chen Cao, Janet H. Hsiao   +4 more
wiley   +1 more source

Noise-aware training of neuromorphic dynamic device networks. [PDF]

Nat Commun
Manneschi L, Vidamour IT, Stenning KD, Swindells C, Venkat G, Griffin D, Gui L, Sonawala D, Donskikh D, Hariga D, Donati E, Stepney S, Branford WR, Gartside JC, Hayward TJ, Ellis MOA, Vasilaki E.   +16 more
europepmc   +1 more source

The state of modelling face processing in humans with deep learning

British Journal of Psychology, EarlyView.
Abstract Deep learning models trained for facial recognition now surpass the highest performing human participants. Recent evidence suggests that they also model some qualitative aspects of face processing in humans. This review compares the current understanding of deep learning models with psychological models of the face processing system ...
P. Jonathon Phillips, David White
wiley   +1 more source

Thermodynamic analysis and intelligent modeling of statin drugs solubility in supercritical carbon dioxide. [PDF]

Sci Rep
Amani M, Shahrabadi A, Ardestani NS.
europepmc   +1 more source

Using multilabel classification neural network to detect intersectional DIF with small sample sizes

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract This study introduces InterDIFNet, a multilabel classification neural network for detecting intersectional differential item functioning (DIF) in educational and psychological assessments, with a focus on small sample sizes. Unlike traditional marginal DIF methods, which often fail to capture the effects of intersecting identities and require ...
Yale Quan, Chun Wang
wiley   +1 more source

Prediction of Compressive Strength of Concrete Using Explainable Machine Learning Models. [PDF]

Materials (Basel)
Fu H, Zhou X, Xu P, Sun D.
europepmc   +1 more source

Artificial intelligence chatbots in endodontic education—Concepts and potential applications

International Endodontic Journal, EarlyView.
Abstract The integration of artificial intelligence (AI) into education is transforming learning across various domains, including dentistry. Endodontic education can significantly benefit from AI chatbots; however, knowledge gaps regarding their potential and limitations hinder their effective utilization.
Hossein Mohammad‐Rahimi, Frank C. Setzer, Anita Aminoshariae, Paul Michael Howell Dummer, Henry F. Duncan, Ali Nosrat   +5 more
wiley   +1 more source

From Experiments to AI: A Comparative Review of Machine Learning Approaches for Predicting Nanofluid Thermophysical Properties. [PDF]

Nanomaterials (Basel)
Al Jadidi S, Moolya R, Padidhapu R, Subramanian S, Moolya S.   +4 more
europepmc   +1 more source